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Algorithmic Medical Robotic Surgical Training and Learning Application

This new medical procedure application trains and learns from training software algorithms by intersecting medical surgical procedures performed by human medical professionals and medical robots. The new application combines algorithms, hardware, non-toxic bacterial secretions, and human beings in the medical surgical profession. Basically the system learns each time the surgical medical procedure compiles data by the intersection of humans and machines. The combination of skilled medical doctors combined with autonomous robots and sometimes drones perform medical surgical procedures on human beings and animals.

Artificial Intelligence Medical Surgical Applications in this patent filing is defined as algorithms that automate medical surgical procedures utilizing both humans, machines and algorithms. Further the Artificial Intelligence Medical Surgical Application or “AI surgical application” is defined as a medical operative or operation method that requires a cut or incision into the skin of a person or animal, to remove, replace, amend or repair body tissues, organs, or other internal parts of the human or animal body.

The AI surgical application works in a method of steps that Trains the application to become autonomous.

Step one: Trains the application or Training of the application by compiling data for all surgical produces which include but are not limited to visual data, fixed picture data, video data, (whereby each movement of the surgical procedure is compiled and converted into data stored on a computer storage device) chatbot or verbal direction from a medical professional during a surgical procedure converted into text and picture data, robotic arms that can be both manually operated or autonomously operated by algorithms, fixed, tethered or free flying manually operated or autonomously operated by algorithms drones, image enlargement devices, computers, CPUs and GPUs and mainframe servers that compute software programs, lighting that is adjusted manually, physically, or autonomous by algorithms or medical human beings, lighting intensity “candle power” manually or autonomously by human beings or machines, nanotechnology devices that are miniature in dimensions and weight (nanometers and nano grams) and a misting system that mists a biosurfactant blend with carriers that limits the spread of sepsis before, during and after the medical procedure, and a tissue and organ abnormal detection system known as a Universal Multipurpose Matter Detection Application “UMMDA” see https://www.de3.ai.

Step Two: Utilize the compiled data from first step to train algorithms on correct, successful surgical results, recognize data that shows incorrect or unsuccessful results, and recognize data that causes errors in all aspects of the application such as an incorrect incision or cut in an organ.

Step Three: Utilize step one data and step two data to train algorithms to become autonomous and operate the surgical operations with human intervention.

Step Four: Utilizing the UMMDA real time tissue and organ abnormal cell and tissue detection application to gain more information of the body to determine real time action.

Step Five: Utilize compiled data from the Biosurfactant applications that deters and/or negates, limits foreign matter such as bacteria, viruses or fungus that infect the animal or human being before, during or after a surgical medical procedure.

The application can utilize different power sources such as direct power (DC) or other types of power such as electricity (AC) or solar, natural gas, wind, nuclear, or water. The application can also utilize a hardware component that is a headset worn by both machines and humans (Doctors) that gathers data during the surgical procedure which includes but is not limited to visual, text, verbal, chemical, light, heat, humidity, wind drafts, atmospheric debris, aerosols in the air of the enclosure where the surgical procedure is taking place, pollutants, contaminates, pathogens, and foreign matter.

In summary, the overall objective is to train the autonomous Artificial Intelligence Medical Surgical Application to operate at a later date without any human intervention.